With conventional mapping techniques, an observer (or his equipment) typically has to have a direct line of sight to an object to be mapped. If a portion of the object is out of sight, it may not be represented in a final map generated with the conventional techniques. This is true for existing mapping techniques such as land survey (with total stations), photo-mapping, photogrammetry, and remote sensing methods.
Many remote-sensing exterior mapping techniques rely on direct reflection of radio-frequency (RF) signals, microwave signals, or other type of signals to detect the presence of objects and to map their locations. For example, an RF signal may be transmitted from a source and directed towards an area of interest, and objects in that area may reflect the RF signal back towards the source. The reflected signals can be collected at the signal source and their time of arrival (TOA) may be used as a basis for determining a relative distance between the source and the reflective objects. This is the general operating principle for radar and sonar. More complex operations might employ two or more transceivers to triangulate object locations.
These remote-sensing mapping techniques, however, suffer from a number of deficiencies. For example, to be accounted for in a final map, an object generally must be within line of sight of at least one transceiver. Even within line of sight, object surfaces that do not reflect a transceiver's signal directly back to that transceiver are effectively “invisible” to the transceiver and therefore will not be charted in the map. Typically, anything other than narrow-angled, single-reflection signals is either not detected or filtered out as noise. As a result, a substantial portion of signals that bounce off an object end up not contributing any geometric information to the final map.
In mapping techniques that are based on a coordinated deployment of signal source(s) and receiver(s), one or more receivers (e.g., transponder tags) may move across an area of interest and simultaneously detect signals from one or more sources. Based on the detected signals, the receivers' coordinates at different locations in the area may be calculated and synthesized into a map. Again, the receiver or tag must typically have a direct line of sight to the signal source(s) in order to accurately determine its own location. In a cluttered environment, such as an urban canyon or an enclosed structure, the receiver or tag may lose direct sight of signals, making it difficult to use direct-path signals for mapping. In this approach, the reflected signals are typically treated as unwanted noise.
Therefore, it has been difficult, if not impossible, to employ conventional mapping techniques in a cluttered environment, such as an urban canyon, or an enclosed structure, such as a building. Such environment or structures tend to generate multipath signals (i.e., signals experiencing one or more reflections between source and detection), making it difficult to rely on direct-path signals alone for the mapping. FIG. 1 illustrates exterior mapping for an exemplary urban environment cluttered with Buildings A, B and C. TC1 and TC2 are two externally located RF transceivers, which may be fixed or mobile transceiver devices. As illustrated in FIG. 1, it may be difficult to employ TC1 and TC2 to map Building C based on existing mapping techniques. Since Buildings A and B are much taller than Building C, the transceivers TC1 and TC2 may have a difficult time gaining an unobstructed sight of Building C. Thus, it is difficult for either TC1 or TC2 to detect any RF signal reflected by Building C. In addition, RF signals from TC1 and TC2 may be reflected one or more times by Buildings A and B (or other objects) before reaching Building C. Therefore, it is also difficult for RF receivers or transponding devices placed on, near or inside Building C to detect direct-path RF signals from TC1 or TC2. In these circumstances, the existing mapping approaches would be incapable of mapping the exterior or interior of Building C, because those approaches either cannot fully exploit geometric information in multipath signals or simply discard multipath signals as unwanted noise. Signals reflecting from the interior surfaces of the building structures are even more difficult to incorporate into the overall mapping process for the same reasons.
Accordingly, there is a need for improved systems and methods that can map a cluttered environment, such as an urban canyon, or an enclosed structure, such as a building, without the aforementioned problems or deficiencies.